CrowdStrike is a global leader in cybersecurity, dedicated to stopping breaches and redefining modern security with advanced AI-native platforms. They are seeking a seasoned Data Engineer to architect and build robust data frameworks that empower their Operational Data Store and Enterprise Data Lake Platforms, collaborating with stakeholders to translate business needs into scalable data solutions.
Responsibilities:
- Lead the full lifecycle of data engineering projects, from initial requirement gathering with stakeholders to production deployment and monitoring
- Design, develop and maintain complex data transformations, ensuring high data quality and performance using scripting languages like Python, Airflow, DBT and databases such as Snowflake or similar Data Lakes
- Build, scale, and maintain automated workflows using Apache Airflow to manage sophisticated data dependencies
- Maintain high engineering standards through CI/CD implementation and rigorous version control using GitHub
- Implement automated processes for data validation, ensuring high standards of data quality, accuracy, and integrity across all pipelines
- Act as a technical partner to the Analytics, Sales, and Marketing teams, building curated datasets that drive strategic decision-making
Requirements:
- 5+ years' experience in design & developing complex automation frameworks, queries, data modeling in SQL, Python, DBT, Apache Airflow
- Deep Experience in scripting languages such as Python and Cloud database experience such as Snowflake, Redshift, etc. to facilitate rapid ingestion and dissemination of key data
- Sales Data Domain Expertise: Hands-on experience working with Sales Pipelines and bookings (Accounts, Opportunity, Role hierarchy, etc), Quota Attainment, RBACs, etc
- Expertise in architecting scalable DBT projects using advanced modeling techniques, custom macros, complex Jinja-templated logic, and modular project structures to enforce DRY (Don't Repeat Yourself) principles across the enterprise
- Advanced proficiency in the DBT lifecycle including CI/CD processes such as Jenkins, Gitlab CI/CD etc., and source control tools such as GitHub, etc
- Experience identifying and solving issues concerning data management to improve data quality, and clean, prepare and optimize data for ingestion and consumption
- Work with internal and external stakeholders to assist with data-related technical issues and support data infrastructure needs
- Proven experience integrating and managing business data from enterprise applications into Semantic Layers to decouple complex logic from the BI layer to drive analytics and insights
- Bachelor's Degree in Computer Science, Information Technology, Computer Engineering, or related IT discipline; or equivalent experience
- Sales Automation Tools Knowledge: Experience with platforms such as Salesforce, People.ai, Clari and CRM systems for data integration and processing
- Understanding of machine learning concepts: Ability to collaborate with data science teams and support machine learning initiatives through data preparation, transformation and Feature store support